Course: Data Centric Architectures credits: 5
- Course code
- SEVM19DCA
- Name
- Data Centric Architectures
- Study year
- 2022-2023
- ECTS credits
- 5
- Language
- English
- Coordinator
- B.J. van der Zwaag
- Modes of delivery
-
- Lecture
- Project-based learning
- Assessments
-
- Data Centric Architectures - Assignment
Learning outcomes
At the end of this module the student is able to:
- Design and/or implement a Digital Signal Processing Architecture considering fixed point core, floating point core, PLD, FPGA, GPU and mixed signal systems.
- Implement algorithms by means of the most suitable programming model (i.e., sequential/linear, functional, parallel)
- Design an IoT system considering edge, fog, cloud or mist computing IoT architectures,
- Design IoT system connectivity considering wireless and wired communication technologies, such as for example: Wifi, mobile G4/G5, LoRa, ethernet, etc.
- Evaluate the impact of system design choices on resource usage considering at least energy consumption and usage of rare materials.
Content
In this module students are trained in architectural design at two conceptual levels. At the level of System Architectures for “big data” applications they learn about top-level trade-offs, e.g. between measured data rates and required processing power.
They get introduced to high-performance computing and streaming database technology. At the level of Digital Signal Processing Architectures, they learn key concepts (fixed point, floating point) and technologies (FPGA, GPU, Mixed signal chips).
Linear and Functional programming as well as Parallel processing are covered.
They get introduced to high-performance computing and streaming database technology. At the level of Digital Signal Processing Architectures, they learn key concepts (fixed point, floating point) and technologies (FPGA, GPU, Mixed signal chips).
Linear and Functional programming as well as Parallel processing are covered.
Included in programme(s)
School(s)
- Institute of Engineering